diff options
| author | CoprDistGit <infra@openeuler.org> | 2023-04-11 03:41:02 +0000 |
|---|---|---|
| committer | CoprDistGit <infra@openeuler.org> | 2023-04-11 03:41:02 +0000 |
| commit | ccca0c903f12fa270958f4f47350dfe93265c301 (patch) | |
| tree | fe08ec5292480c3a319357bddee8ec58706aede1 | |
| parent | 4bc7a760650f5772240b1e39b6209b33ccc32f11 (diff) | |
automatic import of python-qiskit-ignis
| -rw-r--r-- | .gitignore | 1 | ||||
| -rw-r--r-- | python-qiskit-ignis.spec | 615 | ||||
| -rw-r--r-- | sources | 1 |
3 files changed, 617 insertions, 0 deletions
@@ -0,0 +1 @@ +/qiskit-ignis-0.7.1.tar.gz diff --git a/python-qiskit-ignis.spec b/python-qiskit-ignis.spec new file mode 100644 index 0000000..db06c79 --- /dev/null +++ b/python-qiskit-ignis.spec @@ -0,0 +1,615 @@ +%global _empty_manifest_terminate_build 0 +Name: python-qiskit-ignis +Version: 0.7.1 +Release: 1 +Summary: Qiskit tools for quantum information science +License: Apache 2.0 +URL: https://github.com/Qiskit/qiskit-ignis +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/93/d7/a077a5d828037667f4449623ae6c982cac498ebc47e5975ed74c17c15772/qiskit-ignis-0.7.1.tar.gz +BuildArch: noarch + +Requires: python3-numpy +Requires: python3-qiskit-terra +Requires: python3-retworkx +Requires: python3-scipy +Requires: python3-setuptools +Requires: python3-cvxpy +Requires: python3-scikit-learn +Requires: python3-numba +Requires: python3-matplotlib + +%description +# Qiskit Ignis (_DEPRECATED_) + +[](https://opensource.org/licenses/Apache-2.0)[](https://travis-ci.com/Qiskit/qiskit-ignis)[](https://github.com/Qiskit/qiskit-ignis/releases)[](https://pypi.org/project/qiskit-ignis/) + +**_NOTE_** _As of the version 0.7.0 Qiskit Ignis is deprecated and has been +superseded by the +[Qiskit Experiments](https://github.com/Qiskit/qiskit-experiments) project. +Active development on the project has stopped and only compatibility fixes +and other critical bugfixes will be accepted until the project is officially +retired and archived._ + +**Qiskit** is an open-source framework for working with noisy quantum computers at the level of pulses, circuits, and algorithms. + +Qiskit is made up of elements that each work together to enable quantum computing. This element is **Ignis**, which provides tools for quantum hardware verification, noise characterization, and error correction. + +## Migration Guide + +As of version 0.7.0, Qiskit Ignis has been deprecated and some of its functionality +was migrated into the `qiskit-experiments` package and into `qiskit-terra`. + +* Ignis characterization module + + * This module was partly migrated to [`qiskit-experiments`](https://github.com/Qiskit/qiskit-experiments) and split into two different modules: + `qiskit_experiments.library.calibration` + `qiskit_experiments.library.characterization` + * `AmpCal` is now replaced by `FineAmplitude`. + * `ZZFitter` was not migrated yet. + +* Ignis discriminator module + + * This module is in the process of migration to [`qiskit-experiments`](https://github.com/Qiskit/qiskit-experiments) + +* Ignis mitigation module + + * The readout mitigator will be soon added to [`qiskit-terra`](https://github.com/Qiskit/qiskit-terra). + * Experiments for generating the readout mitigators will be added to [`qiskit-experiments`](https://github.com/Qiskit/qiskit-experiments) + * For use of mitigators with `qiskit.algorithms` and the [`QuantumInstance` class](https://qiskit.org/documentation/stubs/qiskit.utils.QuantumInstance.html?highlight=quantuminstance#qiskit.utils.QuantumInstance) + this has been integrated into `qiskit-terra` directly with the `QuantumInstance`. + +* Ignis verification module + + * Randomized benchmarking, Quantum Volume and State and Process Tomography were migrated to [`qiskit-experiments`](https://github.com/Qiskit/qiskit-experiments). + * Migration of Gate-set tomography to [`qiskit-experiments`](https://github.com/Qiskit/qiskit-experiments) is in progress. + * `topological_codes` will continue development under [NCCR-SPIN](https://github.com/NCCR-SPIN/topological_codes/blob/master/README.md), while the functionality is reintegrated into Qiskit. Some additional functionality can also be found in the offshoot project [qtcodes](https://github.com/yaleqc/qtcodes). + * Currently the Accredition and Entanglement modules have not been migrated. +The following table gives a more detailed breakdown that relates the function, as it existed in Ignis, +to where it now lives after this move. + +| Old | New | Library | +| :---: | :---: | :---: | +| qiskit.ignis.characterization.calibrations | qiskit_experiments.library.calibration | qiskit-experiments | +| qiskit.ignis.characterization.coherence | qiskit_experiments.library.characterization | qiskit-experiments | +| qiskit.ignis.mitigation | qiskit_terra.mitigation | qiskit-terra | +| qiskit.ignis.verification.quantum_volume | qiskit_experiments.library.quantum_volume | qiskit-experiments | +| qiskit.ignis.verification.randomized_benchmarking | qiskit_experiments.library.randomized_benchmarking | qiskit-experiments | +| qiskit.ignis.verification.tomography | qiskit_experiments.library.tomography | qiskit-experiments | + +## Installation + +We encourage installing Qiskit via the pip tool (a python package manager). The following command installs the core Qiskit components, including Ignis. + +```bash +pip install qiskit +``` + +Pip will handle all dependencies automatically for us and you will always install the latest (and well-tested) version. + +To install from source, follow the instructions in the [contribution guidelines](./CONTRIBUTING.md). + +### Extra Requirements + +Some functionality has extra optional requirements. If you're going to use any +visualization functions for fitters you'll need to install matplotlib. You +can do this with `pip install matplotlib` or when you install ignis with +`pip install qiskit-ignis[visualization]`. If you're going to use a cvx fitter +for running tomogography you'll need to install cvxpy. You can do this with +`pip install cvxpy` or when you install ignis with +`pip install qiskit-ignis[cvx]`. When performing expectation value measurement +error mitigation using the CTMP method performance can be improved using +just-in-time compiling if Numbda is installed. You can do this with +`pip install numba` or when you install ignis with +`pip install qiskit-ignis[jit]`. For using the discriminator classes in +`qiskit.ignis.measurement` scikit-learn needs to be installed. You can do this with +`pip install scikit-learn` or when you install ignis with +`pip install qiskit-ignis[iq]`. If you want to install all extra requirements +when you install ignis you can run `pip install qiskit-ignis[visualization,cvx,jit,iq]`. + +## Creating your first quantum experiment with Qiskit Ignis +Now that you have Qiskit Ignis installed, you can start creating experiments, to reveal information about the device quality. Here is a basic example: + +``` +$ python +``` + +```python +# Import Qiskit classes +import qiskit +from qiskit import QuantumRegister, QuantumCircuit, ClassicalRegister +from qiskit.providers.aer import noise # import AER noise model + +# Measurement error mitigation functions +from qiskit.ignis.mitigation.measurement import (complete_meas_cal, + CompleteMeasFitter, + MeasurementFilter) + +# Generate a noise model for the qubits +noise_model = noise.NoiseModel() +for qi in range(5): + read_err = noise.errors.readout_error.ReadoutError([[0.75, 0.25],[0.1, 0.9]]) + noise_model.add_readout_error(read_err, [qi]) + +# Generate the measurement calibration circuits +# for running measurement error mitigation +qr = QuantumRegister(5) +meas_cals, state_labels = complete_meas_cal(qubit_list=[2,3,4], qr=qr) + +# Execute the calibration circuits +backend = qiskit.Aer.get_backend('qasm_simulator') +job = qiskit.execute(meas_cals, backend=backend, shots=1000, noise_model=noise_model) +cal_results = job.result() + +# Make a calibration matrix +meas_fitter = CompleteMeasFitter(cal_results, state_labels) + +# Make a 3Q GHZ state +cr = ClassicalRegister(3) +ghz = QuantumCircuit(qr, cr) +ghz.h(qr[2]) +ghz.cx(qr[2], qr[3]) +ghz.cx(qr[3], qr[4]) +ghz.measure(qr[2],cr[0]) +ghz.measure(qr[3],cr[1]) +ghz.measure(qr[4],cr[2]) + +# Execute the GHZ circuit (with the same noise model) +job = qiskit.execute(ghz, backend=backend, shots=1000, noise_model=noise_model) +results = job.result() + +# Results without mitigation +raw_counts = results.get_counts() +print("Results without mitigation:", raw_counts) + +# Create a measurement filter from the calibration matrix +meas_filter = meas_fitter.filter +# Apply the filter to the raw counts to mitigate +# the measurement errors +mitigated_counts = meas_filter.apply(raw_counts) +print("Results with mitigation:", {l:int(mitigated_counts[l]) for l in mitigated_counts}) +``` + +``` +Results without mitigation: {'000': 181, '001': 83, '010': 59, '011': 65, '100': 101, '101': 48, '110': 72, '111': 391} + +Results with mitigation: {'000': 421, '001': 2, '011': 1, '100': 53, '110': 13, '111': 510} +``` + +## Contribution Guidelines + +If you'd like to contribute to Qiskit Ignis, please take a look at our +[contribution guidelines](./CONTRIBUTING.md). This project adheres to Qiskit's [code of conduct](./CODE_OF_CONDUCT.md). By participating, you are expect to uphold to this code. + +We use [GitHub issues](https://github.com/Qiskit/qiskit-ignis/issues) for tracking requests and bugs. Please use our [slack](https://qiskit.slack.com) for discussion and simple questions. To join our Slack community use the [link](https://join.slack.com/t/qiskit/shared_invite/enQtNDc2NjUzMjE4Mzc0LTMwZmE0YTM4ZThiNGJmODkzN2Y2NTNlMDIwYWNjYzA2ZmM1YTRlZGQ3OGM0NjcwMjZkZGE0MTA4MGQ1ZTVmYzk). For questions that are more suited for a forum we use the Qiskit tag in the [Stack Exchange](https://quantumcomputing.stackexchange.com/questions/tagged/qiskit). + +## Next Steps + +Now you're set up and ready to check out some of the other examples from our +[Qiskit Tutorials](https://github.com/Qiskit/qiskit-iqx-tutorials/tree/master/qiskit/advanced/ignis) repository. + +## Authors and Citation + +Qiskit Ignis is the work of [many people](https://github.com/Qiskit/qiskit-ignis/graphs/contributors) who contribute +to the project at different levels. If you use Qiskit, please cite as per the included [BibTeX file](https://github.com/Qiskit/qiskit/blob/master/Qiskit.bib). + +## License + +[Apache License 2.0](LICENSE.txt) + + + + +%package -n python3-qiskit-ignis +Summary: Qiskit tools for quantum information science +Provides: python-qiskit-ignis +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-qiskit-ignis +# Qiskit Ignis (_DEPRECATED_) + +[](https://opensource.org/licenses/Apache-2.0)[](https://travis-ci.com/Qiskit/qiskit-ignis)[](https://github.com/Qiskit/qiskit-ignis/releases)[](https://pypi.org/project/qiskit-ignis/) + +**_NOTE_** _As of the version 0.7.0 Qiskit Ignis is deprecated and has been +superseded by the +[Qiskit Experiments](https://github.com/Qiskit/qiskit-experiments) project. +Active development on the project has stopped and only compatibility fixes +and other critical bugfixes will be accepted until the project is officially +retired and archived._ + +**Qiskit** is an open-source framework for working with noisy quantum computers at the level of pulses, circuits, and algorithms. + +Qiskit is made up of elements that each work together to enable quantum computing. This element is **Ignis**, which provides tools for quantum hardware verification, noise characterization, and error correction. + +## Migration Guide + +As of version 0.7.0, Qiskit Ignis has been deprecated and some of its functionality +was migrated into the `qiskit-experiments` package and into `qiskit-terra`. + +* Ignis characterization module + + * This module was partly migrated to [`qiskit-experiments`](https://github.com/Qiskit/qiskit-experiments) and split into two different modules: + `qiskit_experiments.library.calibration` + `qiskit_experiments.library.characterization` + * `AmpCal` is now replaced by `FineAmplitude`. + * `ZZFitter` was not migrated yet. + +* Ignis discriminator module + + * This module is in the process of migration to [`qiskit-experiments`](https://github.com/Qiskit/qiskit-experiments) + +* Ignis mitigation module + + * The readout mitigator will be soon added to [`qiskit-terra`](https://github.com/Qiskit/qiskit-terra). + * Experiments for generating the readout mitigators will be added to [`qiskit-experiments`](https://github.com/Qiskit/qiskit-experiments) + * For use of mitigators with `qiskit.algorithms` and the [`QuantumInstance` class](https://qiskit.org/documentation/stubs/qiskit.utils.QuantumInstance.html?highlight=quantuminstance#qiskit.utils.QuantumInstance) + this has been integrated into `qiskit-terra` directly with the `QuantumInstance`. + +* Ignis verification module + + * Randomized benchmarking, Quantum Volume and State and Process Tomography were migrated to [`qiskit-experiments`](https://github.com/Qiskit/qiskit-experiments). + * Migration of Gate-set tomography to [`qiskit-experiments`](https://github.com/Qiskit/qiskit-experiments) is in progress. + * `topological_codes` will continue development under [NCCR-SPIN](https://github.com/NCCR-SPIN/topological_codes/blob/master/README.md), while the functionality is reintegrated into Qiskit. Some additional functionality can also be found in the offshoot project [qtcodes](https://github.com/yaleqc/qtcodes). + * Currently the Accredition and Entanglement modules have not been migrated. +The following table gives a more detailed breakdown that relates the function, as it existed in Ignis, +to where it now lives after this move. + +| Old | New | Library | +| :---: | :---: | :---: | +| qiskit.ignis.characterization.calibrations | qiskit_experiments.library.calibration | qiskit-experiments | +| qiskit.ignis.characterization.coherence | qiskit_experiments.library.characterization | qiskit-experiments | +| qiskit.ignis.mitigation | qiskit_terra.mitigation | qiskit-terra | +| qiskit.ignis.verification.quantum_volume | qiskit_experiments.library.quantum_volume | qiskit-experiments | +| qiskit.ignis.verification.randomized_benchmarking | qiskit_experiments.library.randomized_benchmarking | qiskit-experiments | +| qiskit.ignis.verification.tomography | qiskit_experiments.library.tomography | qiskit-experiments | + +## Installation + +We encourage installing Qiskit via the pip tool (a python package manager). The following command installs the core Qiskit components, including Ignis. + +```bash +pip install qiskit +``` + +Pip will handle all dependencies automatically for us and you will always install the latest (and well-tested) version. + +To install from source, follow the instructions in the [contribution guidelines](./CONTRIBUTING.md). + +### Extra Requirements + +Some functionality has extra optional requirements. If you're going to use any +visualization functions for fitters you'll need to install matplotlib. You +can do this with `pip install matplotlib` or when you install ignis with +`pip install qiskit-ignis[visualization]`. If you're going to use a cvx fitter +for running tomogography you'll need to install cvxpy. You can do this with +`pip install cvxpy` or when you install ignis with +`pip install qiskit-ignis[cvx]`. When performing expectation value measurement +error mitigation using the CTMP method performance can be improved using +just-in-time compiling if Numbda is installed. You can do this with +`pip install numba` or when you install ignis with +`pip install qiskit-ignis[jit]`. For using the discriminator classes in +`qiskit.ignis.measurement` scikit-learn needs to be installed. You can do this with +`pip install scikit-learn` or when you install ignis with +`pip install qiskit-ignis[iq]`. If you want to install all extra requirements +when you install ignis you can run `pip install qiskit-ignis[visualization,cvx,jit,iq]`. + +## Creating your first quantum experiment with Qiskit Ignis +Now that you have Qiskit Ignis installed, you can start creating experiments, to reveal information about the device quality. Here is a basic example: + +``` +$ python +``` + +```python +# Import Qiskit classes +import qiskit +from qiskit import QuantumRegister, QuantumCircuit, ClassicalRegister +from qiskit.providers.aer import noise # import AER noise model + +# Measurement error mitigation functions +from qiskit.ignis.mitigation.measurement import (complete_meas_cal, + CompleteMeasFitter, + MeasurementFilter) + +# Generate a noise model for the qubits +noise_model = noise.NoiseModel() +for qi in range(5): + read_err = noise.errors.readout_error.ReadoutError([[0.75, 0.25],[0.1, 0.9]]) + noise_model.add_readout_error(read_err, [qi]) + +# Generate the measurement calibration circuits +# for running measurement error mitigation +qr = QuantumRegister(5) +meas_cals, state_labels = complete_meas_cal(qubit_list=[2,3,4], qr=qr) + +# Execute the calibration circuits +backend = qiskit.Aer.get_backend('qasm_simulator') +job = qiskit.execute(meas_cals, backend=backend, shots=1000, noise_model=noise_model) +cal_results = job.result() + +# Make a calibration matrix +meas_fitter = CompleteMeasFitter(cal_results, state_labels) + +# Make a 3Q GHZ state +cr = ClassicalRegister(3) +ghz = QuantumCircuit(qr, cr) +ghz.h(qr[2]) +ghz.cx(qr[2], qr[3]) +ghz.cx(qr[3], qr[4]) +ghz.measure(qr[2],cr[0]) +ghz.measure(qr[3],cr[1]) +ghz.measure(qr[4],cr[2]) + +# Execute the GHZ circuit (with the same noise model) +job = qiskit.execute(ghz, backend=backend, shots=1000, noise_model=noise_model) +results = job.result() + +# Results without mitigation +raw_counts = results.get_counts() +print("Results without mitigation:", raw_counts) + +# Create a measurement filter from the calibration matrix +meas_filter = meas_fitter.filter +# Apply the filter to the raw counts to mitigate +# the measurement errors +mitigated_counts = meas_filter.apply(raw_counts) +print("Results with mitigation:", {l:int(mitigated_counts[l]) for l in mitigated_counts}) +``` + +``` +Results without mitigation: {'000': 181, '001': 83, '010': 59, '011': 65, '100': 101, '101': 48, '110': 72, '111': 391} + +Results with mitigation: {'000': 421, '001': 2, '011': 1, '100': 53, '110': 13, '111': 510} +``` + +## Contribution Guidelines + +If you'd like to contribute to Qiskit Ignis, please take a look at our +[contribution guidelines](./CONTRIBUTING.md). This project adheres to Qiskit's [code of conduct](./CODE_OF_CONDUCT.md). By participating, you are expect to uphold to this code. + +We use [GitHub issues](https://github.com/Qiskit/qiskit-ignis/issues) for tracking requests and bugs. Please use our [slack](https://qiskit.slack.com) for discussion and simple questions. To join our Slack community use the [link](https://join.slack.com/t/qiskit/shared_invite/enQtNDc2NjUzMjE4Mzc0LTMwZmE0YTM4ZThiNGJmODkzN2Y2NTNlMDIwYWNjYzA2ZmM1YTRlZGQ3OGM0NjcwMjZkZGE0MTA4MGQ1ZTVmYzk). For questions that are more suited for a forum we use the Qiskit tag in the [Stack Exchange](https://quantumcomputing.stackexchange.com/questions/tagged/qiskit). + +## Next Steps + +Now you're set up and ready to check out some of the other examples from our +[Qiskit Tutorials](https://github.com/Qiskit/qiskit-iqx-tutorials/tree/master/qiskit/advanced/ignis) repository. + +## Authors and Citation + +Qiskit Ignis is the work of [many people](https://github.com/Qiskit/qiskit-ignis/graphs/contributors) who contribute +to the project at different levels. If you use Qiskit, please cite as per the included [BibTeX file](https://github.com/Qiskit/qiskit/blob/master/Qiskit.bib). + +## License + +[Apache License 2.0](LICENSE.txt) + + + + +%package help +Summary: Development documents and examples for qiskit-ignis +Provides: python3-qiskit-ignis-doc +%description help +# Qiskit Ignis (_DEPRECATED_) + +[](https://opensource.org/licenses/Apache-2.0)[](https://travis-ci.com/Qiskit/qiskit-ignis)[](https://github.com/Qiskit/qiskit-ignis/releases)[](https://pypi.org/project/qiskit-ignis/) + +**_NOTE_** _As of the version 0.7.0 Qiskit Ignis is deprecated and has been +superseded by the +[Qiskit Experiments](https://github.com/Qiskit/qiskit-experiments) project. +Active development on the project has stopped and only compatibility fixes +and other critical bugfixes will be accepted until the project is officially +retired and archived._ + +**Qiskit** is an open-source framework for working with noisy quantum computers at the level of pulses, circuits, and algorithms. + +Qiskit is made up of elements that each work together to enable quantum computing. This element is **Ignis**, which provides tools for quantum hardware verification, noise characterization, and error correction. + +## Migration Guide + +As of version 0.7.0, Qiskit Ignis has been deprecated and some of its functionality +was migrated into the `qiskit-experiments` package and into `qiskit-terra`. + +* Ignis characterization module + + * This module was partly migrated to [`qiskit-experiments`](https://github.com/Qiskit/qiskit-experiments) and split into two different modules: + `qiskit_experiments.library.calibration` + `qiskit_experiments.library.characterization` + * `AmpCal` is now replaced by `FineAmplitude`. + * `ZZFitter` was not migrated yet. + +* Ignis discriminator module + + * This module is in the process of migration to [`qiskit-experiments`](https://github.com/Qiskit/qiskit-experiments) + +* Ignis mitigation module + + * The readout mitigator will be soon added to [`qiskit-terra`](https://github.com/Qiskit/qiskit-terra). + * Experiments for generating the readout mitigators will be added to [`qiskit-experiments`](https://github.com/Qiskit/qiskit-experiments) + * For use of mitigators with `qiskit.algorithms` and the [`QuantumInstance` class](https://qiskit.org/documentation/stubs/qiskit.utils.QuantumInstance.html?highlight=quantuminstance#qiskit.utils.QuantumInstance) + this has been integrated into `qiskit-terra` directly with the `QuantumInstance`. + +* Ignis verification module + + * Randomized benchmarking, Quantum Volume and State and Process Tomography were migrated to [`qiskit-experiments`](https://github.com/Qiskit/qiskit-experiments). + * Migration of Gate-set tomography to [`qiskit-experiments`](https://github.com/Qiskit/qiskit-experiments) is in progress. + * `topological_codes` will continue development under [NCCR-SPIN](https://github.com/NCCR-SPIN/topological_codes/blob/master/README.md), while the functionality is reintegrated into Qiskit. Some additional functionality can also be found in the offshoot project [qtcodes](https://github.com/yaleqc/qtcodes). + * Currently the Accredition and Entanglement modules have not been migrated. +The following table gives a more detailed breakdown that relates the function, as it existed in Ignis, +to where it now lives after this move. + +| Old | New | Library | +| :---: | :---: | :---: | +| qiskit.ignis.characterization.calibrations | qiskit_experiments.library.calibration | qiskit-experiments | +| qiskit.ignis.characterization.coherence | qiskit_experiments.library.characterization | qiskit-experiments | +| qiskit.ignis.mitigation | qiskit_terra.mitigation | qiskit-terra | +| qiskit.ignis.verification.quantum_volume | qiskit_experiments.library.quantum_volume | qiskit-experiments | +| qiskit.ignis.verification.randomized_benchmarking | qiskit_experiments.library.randomized_benchmarking | qiskit-experiments | +| qiskit.ignis.verification.tomography | qiskit_experiments.library.tomography | qiskit-experiments | + +## Installation + +We encourage installing Qiskit via the pip tool (a python package manager). The following command installs the core Qiskit components, including Ignis. + +```bash +pip install qiskit +``` + +Pip will handle all dependencies automatically for us and you will always install the latest (and well-tested) version. + +To install from source, follow the instructions in the [contribution guidelines](./CONTRIBUTING.md). + +### Extra Requirements + +Some functionality has extra optional requirements. If you're going to use any +visualization functions for fitters you'll need to install matplotlib. You +can do this with `pip install matplotlib` or when you install ignis with +`pip install qiskit-ignis[visualization]`. If you're going to use a cvx fitter +for running tomogography you'll need to install cvxpy. You can do this with +`pip install cvxpy` or when you install ignis with +`pip install qiskit-ignis[cvx]`. When performing expectation value measurement +error mitigation using the CTMP method performance can be improved using +just-in-time compiling if Numbda is installed. You can do this with +`pip install numba` or when you install ignis with +`pip install qiskit-ignis[jit]`. For using the discriminator classes in +`qiskit.ignis.measurement` scikit-learn needs to be installed. You can do this with +`pip install scikit-learn` or when you install ignis with +`pip install qiskit-ignis[iq]`. If you want to install all extra requirements +when you install ignis you can run `pip install qiskit-ignis[visualization,cvx,jit,iq]`. + +## Creating your first quantum experiment with Qiskit Ignis +Now that you have Qiskit Ignis installed, you can start creating experiments, to reveal information about the device quality. Here is a basic example: + +``` +$ python +``` + +```python +# Import Qiskit classes +import qiskit +from qiskit import QuantumRegister, QuantumCircuit, ClassicalRegister +from qiskit.providers.aer import noise # import AER noise model + +# Measurement error mitigation functions +from qiskit.ignis.mitigation.measurement import (complete_meas_cal, + CompleteMeasFitter, + MeasurementFilter) + +# Generate a noise model for the qubits +noise_model = noise.NoiseModel() +for qi in range(5): + read_err = noise.errors.readout_error.ReadoutError([[0.75, 0.25],[0.1, 0.9]]) + noise_model.add_readout_error(read_err, [qi]) + +# Generate the measurement calibration circuits +# for running measurement error mitigation +qr = QuantumRegister(5) +meas_cals, state_labels = complete_meas_cal(qubit_list=[2,3,4], qr=qr) + +# Execute the calibration circuits +backend = qiskit.Aer.get_backend('qasm_simulator') +job = qiskit.execute(meas_cals, backend=backend, shots=1000, noise_model=noise_model) +cal_results = job.result() + +# Make a calibration matrix +meas_fitter = CompleteMeasFitter(cal_results, state_labels) + +# Make a 3Q GHZ state +cr = ClassicalRegister(3) +ghz = QuantumCircuit(qr, cr) +ghz.h(qr[2]) +ghz.cx(qr[2], qr[3]) +ghz.cx(qr[3], qr[4]) +ghz.measure(qr[2],cr[0]) +ghz.measure(qr[3],cr[1]) +ghz.measure(qr[4],cr[2]) + +# Execute the GHZ circuit (with the same noise model) +job = qiskit.execute(ghz, backend=backend, shots=1000, noise_model=noise_model) +results = job.result() + +# Results without mitigation +raw_counts = results.get_counts() +print("Results without mitigation:", raw_counts) + +# Create a measurement filter from the calibration matrix +meas_filter = meas_fitter.filter +# Apply the filter to the raw counts to mitigate +# the measurement errors +mitigated_counts = meas_filter.apply(raw_counts) +print("Results with mitigation:", {l:int(mitigated_counts[l]) for l in mitigated_counts}) +``` + +``` +Results without mitigation: {'000': 181, '001': 83, '010': 59, '011': 65, '100': 101, '101': 48, '110': 72, '111': 391} + +Results with mitigation: {'000': 421, '001': 2, '011': 1, '100': 53, '110': 13, '111': 510} +``` + +## Contribution Guidelines + +If you'd like to contribute to Qiskit Ignis, please take a look at our +[contribution guidelines](./CONTRIBUTING.md). This project adheres to Qiskit's [code of conduct](./CODE_OF_CONDUCT.md). By participating, you are expect to uphold to this code. + +We use [GitHub issues](https://github.com/Qiskit/qiskit-ignis/issues) for tracking requests and bugs. Please use our [slack](https://qiskit.slack.com) for discussion and simple questions. To join our Slack community use the [link](https://join.slack.com/t/qiskit/shared_invite/enQtNDc2NjUzMjE4Mzc0LTMwZmE0YTM4ZThiNGJmODkzN2Y2NTNlMDIwYWNjYzA2ZmM1YTRlZGQ3OGM0NjcwMjZkZGE0MTA4MGQ1ZTVmYzk). For questions that are more suited for a forum we use the Qiskit tag in the [Stack Exchange](https://quantumcomputing.stackexchange.com/questions/tagged/qiskit). + +## Next Steps + +Now you're set up and ready to check out some of the other examples from our +[Qiskit Tutorials](https://github.com/Qiskit/qiskit-iqx-tutorials/tree/master/qiskit/advanced/ignis) repository. + +## Authors and Citation + +Qiskit Ignis is the work of [many people](https://github.com/Qiskit/qiskit-ignis/graphs/contributors) who contribute +to the project at different levels. If you use Qiskit, please cite as per the included [BibTeX file](https://github.com/Qiskit/qiskit/blob/master/Qiskit.bib). + +## License + +[Apache License 2.0](LICENSE.txt) + + + + +%prep +%autosetup -n qiskit-ignis-0.7.1 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-qiskit-ignis -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Tue Apr 11 2023 Python_Bot <Python_Bot@openeuler.org> - 0.7.1-1 +- Package Spec generated @@ -0,0 +1 @@ +55a8e6a97f1c62d1f4dcb82c880fba7a qiskit-ignis-0.7.1.tar.gz |